Volume 14 | Issue 2 |

 Abstract

A study with quasi-experimental one group pre-test-post-test design was used to assess the effectiveness of structured teaching programme on knowledge regarding ill effect of plastic on health among the community people of Andharua, Jagganathprasad, Bhubaneswar. In this study community people were selected by using simple random sampling technique and data were collected by using self-structured questionnaire method. Demographic variables reveals that 23 community people were male whereas 7 community people were female. From the pre-test and post-test knowledge scores, it was found that in pre-test 20% of people had poor level of knowledge whereas none of them in post-test.70% of people had average level of knowledge in pre-test while 6.7% in post-test.10% of people had good level of knowledge in pre-test whereas 33.3% in post-test.In pre-test none of them had excellent level of knowledge whereas almost i.e. 60% in post-test. At the end, it is concluded that maximum people had poor and average knowledge in pre-test whereas maximum people had good and excellent knowledge in post-test. Therefore, it is interpreted that post-test scores were astonishingly much more than the pre-test scores after implementing the structured teaching programme. The difference in paired pre-test and post-test is (-485). This indicates an increase in knowledge scores after implementing structured teaching programme and calculated value of 't' (29): 15.88 was found highly significant at 0.05 level of significance. Association between the level of knowledge among the community people was highly significant with their age and significant with their education and not significant with gender, family income, occupation, types of family, method of waste disposal and previous source of knowledge.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

STRUCTURE TEACHING PROGRAM ,ILL EFFECT, PLASTIC, COMMUNITY

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Serverless computing (Function-as-a-Service, FaaS) is severely limited by the COLD start problem, a latency penalty incurred during container initialization. Current mitigation approaches, relying primarily on static keep-alive policies or single-source time-series prediction, fail to balance performance consistency with resource cost, often leading to a 40-60% waste in resource provisioning. We introduce COLDSTART (Cost- and Latency-Optimized Serverless Orchestration via Multi-Modal Prediction and Confidence-Based Warming), a novel, intelligent orchestration framework designed to minimize COLD start occurrences and resource overhead simultaneously. Our core contribution is a Multi-Modal Prediction (MMP) architecture that fuses six heterogeneous data streams--spanning user behavior, API metrics, and system telemetry--into a unified feature space. This space is analyzed by a tri-model Ensemble Learning Engine (XGBoost, LSTM, and Transformer) to generate highly accurate invocation forecasts. Crucially, we propose a Confidence-Based Warming (CBW) mechanism that gates resource allocation based on a calculated prediction confidence score (C), thereby minimizing expensive false positives. Through extensive experimentation on simulated production workloads, COLDSTART achieved a 68% reduction in COLD starts and improved 95th percentile latency to under 200 ms, concurrently delivering a 45% reduction in operational waste compared to single-source ML baselines. This work demonstrates a robust, context-aware solution essential for sustainable and high-performance serverless deployments. Index Terms--Serverless Computing, Function-as-a-Service (FaaS), COLD Start Mitigation, Multi-Modal Prediction, Ensemble Learning, Cost Optimization, Proactive Warming.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Serverless Computing, Cold Start Mitigation, Function-as-a-Service (FaaS), Multi-Modal Prediction, Ensemble Learning, Confidence-Based Warming, Cost Optimization, Latency Optimization

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In this modern digital era, interface design has transformed from static to dynamic interactions, where motion plays an important role in guiding user experience. Motion and animation has no longer restricted to decorative functions; Rather than, they act as narrative medium that leads users, visualize meanings, and enhance emotional involvement. This paper observes motion as narrative in interface design, concentrating on how storytelling is crafted through animation, transitions, feedback and micro-interactions Anchored in Narrative Theory, the study examines user interactions as narrative sequence in which motion organize the initiation, development, and resolution of tasks. Guided by qualitative and descriptive case study methodology, the study focus on digital platforms such as Duolingo, Airbnb, and Google's Material Design to explain how narrative motion shapes onboaring, navigation, feedback, and brand experience. These findings highlights that well-designed motion amplifies clarity, stability, usability and emotional engagement, while overused or poorly implemented motion may lead to inclusive design and performance challenges. The study highlights that narrative motion is an effective design strategy that connects functionality and experience, with growing conceptual importance in AI-driven personalization and immersive AR and VR environments.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Interface Design, Human-Computer Interaction (HCI), Digital Storytelling, Motion Design, Narrative Theory, Animation, User Experience, Immersive Interfaces

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The present seasonal study was conducted in the Gorja Lake near Bhadrawati. Monthly and seasonal variation in the biological parameters for phytoplanktonic study like Chlorophyceae in Gorja lake were studied during the study period of June 2024 to May 2025 in which 17 species were recorded. This study indicates that the lakes of central India exhibit substantial variation in their biotic and abiotic characteristics.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Gorja lake, Chlorophyceae diversity, Phytoplankton.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rapid increase in global energy demand, driven by industrialization, urbanization, and technological advancements, has resulted in excessive dependence on conventional fossil fuels. However, the extensive use of coal, oil, and natural gas has led to serious environmental concerns, such as greenhouse gas emissions, climate change, air pollution, and resource depletion. Sustainable energy sources provide cleaner and renewable alternatives that can meet energy requirements while minimizing environmental impact. This study examined major sustainable energy sources, including solar, wind, hydropower, biomass, tidal, and geothermal energy. It analyzes their working principles, advantages, limitations, technological developments, and economic implications. This paper also highlights the challenges of large-scale adoption and suggests strategies for promoting a global sustainable energy transition

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Sustainable energy, renewable energy, clean energy, climate change, smart grid, energy transition.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

With the rapid growth of urbanization, the number of vehicles on the road has significantly increased, leading to a growing demand for efficient parking solutions. One of the major challenges faced by by drivers in urban areas is the unavailability of parking spaces, especially during peak hours. This often results in excessive time spent searching for parking, fuel wastage, trafie congestion, and environmental pollution. This project proposes the design and implementation of a Smart Parking System using Arduino and Infrared (IR) sensors to detect the occupancy status of parking slots in real time. Each parking lane is equipped with IR sensors that monitor the availability of slots and relay this Information a microcontroller (Arduino). The data is then displayed on a user interface device, such as an LCD or mobile application, helping drivers to quickly identify and navigate to available parking spots. The system aims to minimize the time and effort required to find parking, reduce fuel consumption, and lower environmental pollution. It is a low- low-cost, scalable, and efficient solution suitable for for public and private parking facilities, The proposed smart parking system enhances urban mobility and contributes to the development of smarter and more sustainable

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Index Terms-Smart Parking System. Arduino, IR Sensors, Parking Slot Detection, Urban Transportation, Real-time Mon-itoring, Environmental Pollution, Fuel Wastage, Traffic Man agement, loT-based Parking, Cost-effective Solution, Sustainable Mobility L

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

A 11year-old female patient with a history of Global Developmental Delay (GDD) presented with uncontrolled Generalized tonic-clonic seizures (GTCS) despite being on anti-epileptic therapy. Breakthrough seizures were noted in the setting of recent illness and poor medication adherence.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

GTCS, Global Developmental Delay, Breakthrough seizures, Epilepsy, Paediatric neurology.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Asset management plays a crucial role in determining the developmental impact and long-term sustainability of Self Help Groups (SHGs). Proper identification, utilization and maintenance of assets enable SHGs to strengthen income-generating activities and improve the socio-economic conditions of their members. The present study examines the effectiveness of asset management practices of Self Help Groups in Bangalore Urban District and analyses their relationship with developmental outcomes. The study is based on primary data collected from 120 SHG members using a structured questionnaire. Statistical tools such as mean, standard deviation, correlation analysis and descriptive analysis were employed. The findings reveal a strong positive relationship between effective asset management and developmental activities of SHGs. The study concludes that systematic asset management significantly contributes to economic empowerment and sustainability of SHGs.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Asset Management, Developmental Outcomes, Financial Management, Self Help Groups, Bangalore Urban

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Nanoboats represent a cutting edge class of nanoscale delivery vehicles inspired by biological propulsion mechanisms and engineered for enhanced targeting, controlled release, and precision therapy. These nanosystems integrate navigation strategies derived from motor proteins, synthetic swimmers, and nano propellers with advanced drug encapsulation techniques to traverse physiological barriers. This review synthesizes recent advances in nanoboat design, propulsion mechanisms, therapeutic payload integration, targeting strategies, and clinical translation challenges. We discuss key propulsion technologies -- from catalytic and magnetic fields to biohybrid designs -- and analyze their impact on delivery efficiency, tissue specificity, and biocompatibility. Finally, we assess current limitations, safety concerns, and future directions in harnessing nanoboat systems for targeted cancer therapy, neurological treatments, and personalized medicine applications.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Nanoboats , Drug delivery , Molecular propulsion , Precision therapy , Targeted delivery , Biohybrid nanoswimmers

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The "PreCare" platform is an intelligent healthcare solution designed to mitigate the financial uncertainty associated with oncological care. By leveraging Random Forest Regression, the system analyses patient-specific variables--such as age, cancer type, and diagnostic stage--to provide precise, data-driven treatment cost estimates. Developed using React.js for the frontend and Flask for the backend, the platform seamlessly integrates hospital recommendations and educational resources. This research addresses the lack of transparency in traditional medical billing by replacing manual estimations with a reliable automated framework. Experimental results demonstrate that PreCare enhances financial preparedness and accessibility, with future iterations aimed at incorporating insurance analytics and NLP-driven patient support.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Machine Learning, Healthcare Analytics, Random Forest Regression, Cost Estimation, AI in Healthcare, Medical Decision Support.

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Creative Commons Attribution 4.0 and The Open Definition